Abstract: Systems and methods are directed to email threading based on machine learning determined categories and features. A network system accesses a plurality of emails addressed to a user. The network system then classifies, using a machine learning model, each email into at least one of a plurality of categories. For a category of the plurality of categories, one or more feature values are extracted from each email in the category. Based on the category and the extracted feature values, the network system groups messages having a same feature value in the same category together into a single email thread. Information related to the single email thread is then presented at a client device of the user.

Abstract: Systems and methods are directed to email threading based on machine learning determined categories and features. A network system accesses a plurality of emails addressed to a user. The network system then classifies, using a machine learning model, each email into at least one of a plurality of categories. For a category of the plurality of categories, one or more feature values are extracted from each email in the category. Based on the category and the extracted feature values, the network system groups messages having a same feature value in the same category together into a single email thread. Information related to the single email thread is then presented at a client device of the user.

Abstract: Aggregation of content based on user-generated topics is provided. Users may associate one or more topics with content items stored across various workloads and repositories. A topic may be a word or phrase of the user's choice, and may be utilized for discoverability of information and aggregation of content items. Topics and content items associated with topics may be acted on (e.g., a user may add or delete topics to associate with a content item, associate or disassociate content items with a topic, embed a set of content items or a stream of content items associated with a topic into other experiences, follow topics, etc.). Content items identified as related to a specific topic may be automatically suggested as possible content items of interest to the user. Additionally, when a user follows a topic, the user may be notified of any changes that occur to the topic.

Abstract: Systems and methods for facilitating an enterprise user to obtain an answer to a user question within an enterprise based on an enterprise knowledge graph are provided. In particular, an enterprise server may receive the user question from the enterprise user, determine a suggested topic associated with the user question based on the enterprise knowledge graph by transforming the user question into a semantic representation to identify a plurality of similar entities within the enterprise knowledge graph, and determine whether a relevant question-and-answer (Q&A) pair linked to the suggested topic exists based on the enterprise knowledge graph. In response to a determination that the relevant Q&A pair does not exist, the enterprise server may determine a predicted answer to the user question and update the enterprise knowledge graph.

Abstract: A content creation application can include a feature that receives an inline note within a document and communicates the content of the inline note and a user identifier associated with an author of the inline note to an intelligence service. The intelligence service can identify, from the content of the inline note, one or more agents and a request, the identified one or more agents being the author, one or more person agents, one or more bot agents, or a combination thereof. Based on the identified agent (or lack thereof), the intelligence service can generate a message to each of the one or more agents and communicate the message to the each of the one or more agents over a communication channel. A person agent or the author can receive the message and view the message using the appropriate communication application without accessing the original document.

Abstract: In non-limiting examples of the present disclosure, systems, methods and devices for exposing computing service skills are presented. A task intent associated with a natural language input may be identified. A plurality of add-in matching language models may be applied to the natural language input, wherein each add-in matching language model corresponds to a computing service skill. A score for each of the computing service skills may be generated. Each of the computing service skills may be ranked. A selectable option to execute an add-in associated with a top ranked computing service skill may be caused to be displayed. An indication that a selection of the option has been made may be received. The add-in associated with the top ranked computing service skill may be executed.

Abstract: In non-limiting examples of the present disclosure, systems, methods and devices for exposing computing service skills are presented. A task intent associated with a natural language input may be identified. A plurality of add-in matching language models may be applied to the natural language input, wherein each add-in matching language model corresponds to a computing service skill. A score for each of the computing service skills may be generated. Each of the computing service skills may be ranked. A selectable option to execute an add-in associated with a top ranked computing service skill may be caused to be displayed. An indication that a selection of the option has been made may be received. The add-in associated with the top ranked computing service skill may be executed.

Abstract: Aggregation of content based on user-generated topics is provided. Users may associate one or more topics with content items stored across various workloads and repositories. A topic may be a word or phrase of the user's choice, and may be utilized for discoverability of information and aggregation of content items. Topics and content items associated with topics may be acted on (e.g., a user may add or delete topics to associate with a content item, associate or disassociate content items with a topic, embed a set of content items or a stream of content items associated with a topic into other experiences, follow topics, etc.). Content items identified as related to a specific topic may be automatically suggested as possible content items of interest to the user. Additionally, when a user follows a topic, the user may be notified of any changes that occur to the topic.

Abstract: Techniques directed to applying metadata to content items are described herein. The techniques may include displaying a graphical element associated with a metadata attribute(s) and displaying a visual representation for a content item(s). The graphical element may be associated with a group of content items that have a common metadata attribute. In some instances, the graphical element may be dragged and dropped onto the visual representation to associate the content item(s) with the metadata attribute(s). In other instances, the visual representation may be dragged and dropped on the graphical element to associate the content item(s) with the metadata attribute(s).

Abstract: Systems, methods, and software are disclosed herein for indicating a change to content in a document to a user. A document is displayed in a user interface to an application. Content then is introduced into the document from a source external to the document. After the content has been introduced into the document, the source of the content is queried for any changes to the content at the source. If a change has occurred, an indication of the change to the content at the source is introduced in the document.

Abstract: Aggregation of content based on user-generated topics is provided. Users may associate one or more topics with content items stored across various workloads and repositories. A topic may be a word or phrase of the user's choice, and may be utilized for discoverability of information and aggregation of content items. Topics and content items associated with topics may be acted on (e.g., a user may add or delete topics to associate with a content item, associate or disassociate content items with a topic, embed a set of content items or a stream of content items associated with a topic into other experiences, follow topics, etc.). Content items identified as related to a specific topic may be automatically suggested as possible content items of interest to the user. Additionally, when a user follows a topic, the user may be notified of any changes that occur to the topic.

Abstract: Application programming interfaces (APIs) are provided that provide functionality of accessing, ranking, scoping, enrichment, cleansing, and cohort determination of content based on a corpus of trusted sources. For example, in response to receiving a request for ranked objects via a ranking API, a system can obtain objects from a corpus identified by the request for ranked objects and a corresponding rank and/or score of each of the objects and provide the objects and the corresponding rank and/or score of each of the objects to a source of the request for ranked objects, wherein the corpus stores identified trusted sources that are scored based at least on a document activity score.

Abstract: Non-limiting examples of the present disclosure relate to fidelity management of an exemplary notecard item based on action(s) for movement that may re-locate notecard item(s) across any of: different content portions of a digital document, different digital documents of an application/service and digital documents of different applications/services. Specific data (and metadata) is collected and analyzed to enable determination of a level of fidelity for rendering of a notecard item, where a representation of a notecard item is generated to fit a context of a digital document in which the notecard item is being placed. A representation of a notecard item may be rendered at a first level of fidelity in one context but a different level of fidelity when the notecard item is moved to a different context. In other instances, evaluation of a notecard item yields a determination to maintain fidelity after an action that re-locates a notecard item.

Abstract: Application programming interfaces (APIs) are provided that provide functionality of accessing, ranking, scoping, enrichment, cleansing, and cohort determination of content based on a corpus of trusted sources. For example, in response to receiving a request for ranked objects via a ranking API, a system can obtain objects from a corpus identified by the request for ranked objects and a corresponding rank and/or score of each of the objects and provide the objects and the corresponding rank and/or score of each of the objects to a source of the request for ranked objects, wherein the corpus stores identified trusted sources that are scored based at least on a document activity score.

Abstract: Non-limiting examples of the present disclosure relate to creation and management of exemplary notecard items that are reusable in different contexts and across different applications/services. Exemplary notecard items may be created and presented through a user interface of an application/service. A notecard item is individual, self-contained digital data object that provides content to supplement a digital document. Exemplary notecard items live outside of an application/service, in which the notecard item is created or used, where a notecard item may be linked to a digital document but also exists as a separate object. For instance, an exemplary notecard file may be created for management of a created notecard item, where the notecard file is stored in one or more data storages (e.g., a local cache of a computing device and/or a distributed data storage) that is accessible by applications/services.

Abstract: Non-limiting examples of the present disclosure relate to fidelity management of an exemplary notecard item based on action(s) for movement that may re-locate notecard item(s) across any of: different content portions of a digital document, different digital documents of an application/service and digital documents of different applications/services. Specific data (and metadata) is collected and analyzed to enable determination of a level of fidelity for rendering of a notecard item, where a representation of a notecard item is generated to fit a context of a digital document in which the notecard item is being placed. A representation of a notecard item may be rendered at a first level of fidelity in one context but a different level of fidelity when the notecard item is moved to a different context. In other instances, evaluation of a notecard item yields a determination to maintain fidelity after an action that re-locates a notecard item.

Abstract: Non-limiting examples of the present disclosure relate to creation and management of exemplary notecard items that are reusable in different contexts and across different applications/services. Exemplary notecard items may be created and presented through a user interface of an application/service. A notecard item is individual, self-contained digital data object that provides content to supplement a digital document. Exemplary notecard items live outside of an application/service, in which the notecard item is created or used, where a notecard item may be linked to a digital document but also exists as a separate object. For instance, an exemplary notecard file may be created for management of a created notecard item, where the notecard file is stored in one or more data storages (e.g., a local cache of a computing device and/or a distributed data storage) that is accessible by applications/services.

Abstract: Described herein is a system and method for invoking a service using a trigger entry. During editing of a document, a trigger entry that is based upon content added to the document is received. Responsive to receipt of the trigger entry, information regarding one or more services (e.g., local and/or remote) is provided with selection of a service received from a user. The selected service is then invoked with information from the selected service provided to the user and/or information received from the user provided to the selected service (e.g., in real-time).

Abstract: Systems and method for routing search query results in a networked computing environment. An initial search query is reformulated into at least one sub-query in accordance with one or more configurable rules. The sub-query is sent to at least one information system or source, and any potential hits associated with the same are optionally combined and then rendered for viewing.

Abstract: Context from a content creation application is used to focus both on the types of files and the types of content searched by a search application, as well as the type of results provided to the content creation application for use by the user, instead of simply improving relevancy of a result. A query of structured, contextual information can be formulated based on the discernable intent and context information provided with the request. Queries are sent to search applications to search appropriate file types and/or content types. Context-sensitive results returned from the search application(s) can be grouped by performing a clustering process according to semantic similarity in order to group the context-sensitive results into groups, and selected ones of the context-sensitive results can be provided to a user.